Enabling multi-segment 5G service provisioning and maintenance through network slicing

This is a post-peer-review, pre-copyedit version of an article published in Journal of Network and Systems Management . The final authenticated version is available online at: http://dx.doi.org/10.1007/s10922-019-09509-9The current deployment of 5G networks in a way to support the highly demanding service types defined for 5G, has brought the need for using new techniques to accommodate legacy networks to such requirements. Network Slicing in turn, enables sharing the same underlying physical infrastructure among services with different requirements, thus providing a level of isolation between them to guarantee their proper functionality. In this work, we analyse from an architectural point of view, the required coordination for the provisioning of 5G services over multiple network segments/domains by means of network slicing, considering as well the use of sensors and actuators to maintain slices performance during its lifetime. We set up an experimental multi-segment testbed to demonstrate end-to-end service provisioning and its guarantee in terms of specific QoS parameters, such as latency, throughput and Virtual Network Function (VNF) CPU/RAM consumption. The results provided, demonstrate the workflow between different network components to coordinate the deployment of slices, besides providing a set of examples for slice maintenance through service monitoring and the use of policy-based actuations.Peer ReviewedPostprint (author's final draft

Orchestration in the Cloud-to-Things Compute Continuum: Taxonomy, Survey and Future Directions

IoT systems are becoming an essential part of our environment. Smart cities, smart manufacturing, augmented reality, and self-driving cars are just some examples of the wide range of domains, where the applicability of such systems has been increasing rapidly. These IoT use cases often require simultaneous access to geographically distributed arrays of sensors, and heterogeneous remote, local as well as multi-cloud computational resources. This gives birth to the extended Cloud-to-Things computing paradigm. The emergence of this new paradigm raised the quintessential need to extend the orchestration requirements i.e., the automated deployment and run-time management) of applications from the centralised cloud-only environment to the entire spectrum of resources in the Cloud-to-Things continuum. In order to cope with this requirement, in the last few years, there has been a lot of attention to the development of orchestration systems in both industry and academic environments. This paper is an attempt to gather the research conducted in the orchestration for the Cloud-to-Things continuum landscape and to propose a detailed taxonomy, which is then used to critically review the landscape of existing research work. We finally discuss the key challenges that require further attention and also present a conceptual framework based on the conducted analysis.Comment: Journal of Cloud Computing Pages: 2

A Model-Based Abstraction Layer for Heterogeneous SDN Applications

Modern controllers for software-defined networks (SDN) enable the execution of arbitrary SDN applications (eg, Network Address Translation (NAT), traffic monitors) that may be exploited by an overarching set of services (eg, application-layer orchestrators) to build even richer services. To this purpose, the above overarching services require a mechanism that allows reading the run-time state and writing the configuration of arbitrary SDN applications, possibly through a uniform API. Unfortunately, most SDN applications are not designed/implemented by taking into account the possibility to be used as part of higher level service workflows (eg, a complex intrusion prevention system that leverages multiple elementary services as individual components), hence they may not provide an adequate interface that would allow overarching services to exploit their features. This paper addresses this problem by proposing an approach to represent the run-time state of arbitrary applications, where data are exported according to high-level model-based structures. Furthermore, the mapping from the high-level data model to the actual data representation within the SDN application is enabled by a suite of algorithms that are generic enough to operate independently of the actual source code of the application, thus avoiding undesired and invasive modifications to existing applications. The paper also presents a software framework and a prototype implementing the proposed approach, characterizes the resulting performance, and discusses pros and cons of the proposed approach

IoT@run-time: a model-based approach to support deployment and self-adaptations in IoT systems

Today, most Internet of Things (IoT) systems leverage edge and fog computing to meet increasingly restrictive requirements and improve quality of service (QoS). Although these multi-layer architectures can improve system performance, their design is challenging because the dynamic and changing IoT environment can impact the QoS and system operation. In this thesis, we propose a modeling-based approach that addresses the limitations of existing studies to support the design, deployment, and management of self-adaptive IoT systems. We have designed a domain specific language (DSL) to specify the self-adaptive IoT system, a code generator that generates YAML manifests for the deployment of the IoT system, and a framework based on the MAPE-K loop to monitor and adapt the IoT system at runtime. Finally, we have conducted several experimental studies to validate the expressiveness and usability of the DSL and to evaluate the ability and performance of our framework to address the growth of concurrent adaptations on an IoT system.Hoy en día, la mayoría de los sistemas de internet de las cosas (IoT, por su sigla en inglés) aprovechan la computación en el borde (edge computing) y la computación en la niebla (fog computing) para cumplir requisitos cada vez más restrictivos y mejorar la calidad del servicio. Aunque estas arquitecturas multicapa pueden mejorar el rendimiento del sistema, diseñarlas supone un reto debido a que el entorno de IoT dinámico y cambiante puede afectar a la calidad del servicio y al funcionamiento del sistema. En esta tesis proponemos un enfoque basado en el modelado que aborda las limitaciones de los estudios existentes para dar soporte en el diseño, el despliegue y la gestión de sistemas de IoT autoadaptables. Hemos diseñado un lenguaje de dominio específico (DSL) para modelar el sistema de IoT autoadaptable, un generador de código que produce manifiestos YAML para el despliegue del sistema de IoT y un marco basado en el bucle MAPE-K para monitorizar y adaptar el sistema de IoT en tiempo de ejecución. Por último, hemos llevado a cabo varios estudios experimentales para validar la expresividad y usabilidad del DSL y evaluar la capacidad y el rendimiento de nuestro marco para abordar el crecimiento de las adaptaciones concurrentes en un sistema de IoT.Avui dia, la majoria dels sistemes d'internet de les coses (IoT, per la sigla en anglès) aprofiten la informàtica a la perifèria (edge computing) i la informàtica a la boira (fog computing) per complir requisits cada cop més restrictius i millorar la qualitat del servei. Tot i que aquestes arquitectures multicapa poden millorar el rendiment del sistema, dissenyar-les suposa un repte perquè l'entorn d'IoT dinàmic i canviant pot afectar la qualitat del servei i el funcionament del sistema. En aquesta tesi proposem un enfocament basat en el modelatge que aborda les limitacions dels estudis existents per donar suport al disseny, el desplegament i la gestió de sistemes d'IoT autoadaptatius. Hem dissenyat un llenguatge de domini específic (DSL) per modelar el sistema d'IoT autoadaptatiu, un generador de codi que produeix manifestos YAML per al desplegament del sistema d'IoT i un marc basat en el bucle MAPE-K per monitorar i adaptar el sistema d'IoT en temps d'execució. Finalment, hem dut a terme diversos estudis experimentals per validar l'expressivitat i la usabilitat del DSL i avaluar la capacitat i el rendiment del nostre marc per abordar el creixement de les adaptacions concurrents en un sistema d'IoT.Tecnologies de la informació i de xarxe

Design and Implementation of a Generalized Resource Management Architecture in the TeMoto Software Framework

Autonomous robots are utilized in a wide range of domains, combining a large number of resources like sensors, actuators and algorithms to form a self-acting robotic system. Tools, such as ROS and TeMoto, have been developed to allow for handling and managing of resources composing such systems. While TeMoto is meant to handle dynamic and changing situations the current implementation of its Resource Registrar, a core TeMoto component tasked with allocating, deallocating and tracking of resources, is tightly coupled to ROS, making it difficult to modify and improve. As a result of this thesis, the Resource Registrar (RR) of TeMoto was completely redesigned to be extendable to other robotic middleware, such as ROS2, and to improve TeMoto’s robustness with features, e.g., full recovery of the RR, that were unattainable with the previous design

AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0

The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity beyond jobs and growth. HCAI presents new objectives that were unreachable by either humans or machines alone, but this also comes with a new set of challenges. Our proposed method accomplishes this through the knowlEdge architecture, which enables human operators to implement AI solutions using a zero-touch framework. It relies on containerized AI model training and execution, supported by a robust data pipeline and rounded off with human feedback and evaluation interfaces. The result is a platform built from a number of components, spanning all major areas of the AI lifecycle. We outline both the architectural concepts and implementation guidelines and explain how they advance HCAI systems and Industry 5.0. In this article, we address the problems we encountered while implementing the ideas within the edge-to-cloud continuum. Further improvements to our approach may enhance the use of AI in Industry 5.0 and strengthen trust in AI systems

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

The Internet of Things, fog and cloud continuum: Integration and challenges

The Internet of Things needs for computing power and storage are expected to remain on the rise in the next decade. Consequently, the amount of data generated by devices at the edge of the network will also grow. While cloud computing has been an established and effective way of acquiring computation and storage as a service to many applications, it may not be suitable to handle the myriad of data from IoT devices and fulfill largely heterogeneous application requirements. Fog computing has been developed to lie between IoT and the cloud, providing a hierarchy of computing power that can collect, aggregate, and process data from/to IoT devices. Combining fog and cloud may reduce data transfers and communication bottlenecks to the cloud and also contribute to reduced latencies, as fog computing resources exist closer to the edge. This paper examines this IoT-Fog-Cloud ecosystem and provides a literature review from different facets of it: how it can be organized, how management is being addressed, and how applications can benefit from it. Lastly, we present challenging issues yet to be addressed in IoT-Fog-Cloud infrastructures

LAIX-score : a design framework for live audience interaction management systems

This study focuses on computer-supported live audience interaction. In conventional lectures audience interacts explicitly with the performer for example by waving hand and asking question directly or clapping hands. For decades, non digital audience response systems have enabled simple multiple option audience interaction patterns. Modern mobile personal computing devices, digital projectors, wireless networks and real time software platforms enable creation of new kinds of interaction patterns that can significantly increase the amount of audience interaction during events. Audience interaction can make events for example more engaging and productive. This research presents a design framework for computer-supported live audience interaction called the LAIX-score. LAIX stands for Live Audience Interac(X)tion and the “score” refers to the musical notation language. Musical notation has been an inspiration for the development of the framework and illustrates how LAIX-score is intended as generic and practical framework for coordinating live audience interaction similarly as musical notation is generic and practical framework for coordinating musical performances. However, while musical notation is important inspiration, it is not the core reference for the LAIX-score. LAIX-score core references are the live audio mixing and live light control frameworks, which are technologyenabled frameworks for supporting and producing live performances. The LAIX-score framework is composed of five core elements: Interaction activities, interface channels, state control matrix, temporal management of interactions and participant’s identity management. These five core elements compose a concrete and comprehensive framework that can be directly applied in the design of live audience interaction management system and in the development of live audience interaction production practices. The research is a constructive and practice-led in the wild research (Chapter 2) that borrows aspects from design research, artistic research and human-computer interaction research. The LAIX-score framework is based on three core requirements identified during a five years of practice-led domain exploration (Chapter 3). (Requirement 1) Live audience interaction must support different kinds of interaction patterns. Hence, the framework should acknowledge that live audience interaction is more than questions and answers (Q&A) and poll type interaction patterns. (Requirement 2) Live audience interaction must support different roles. Hence, the role configuration in live audience interaction can include several different performer, audience and orchestrator roles. (Requirement 3) Live audience interaction framework must also support different kinds and parallel functions live audience interaction function. Hence, in the same event production live audience interaction may be used for example for audience activation, workshop facilitation, participatory decision making and catalyzing social networking, and these functions may take place concurrently. None of the existing live audience interaction systems satisfy all of the core requirements. This is explained in more detail in Section 4.2. Lack of adequate designs that meets the above mentioned criterias justifies the development of a new design framework. The LAIX-score (Chapter 5) follows a two dimensional matrix type control framework, which is called state control matrix. Also the core references, live audio mixing and live light control (Sections 4.3 –4.5), have similar control framework. Rows in the state control matrix are called as interaction activities. Columns in the state control matrix are interface channels, which is the system equivalent for supporting different roles and user interfaces (requirement 2). The matrix is used for visibility control of the interaction activities. The visibility of interaction activities can be manipulated independently in each interface channel. The matrix form satisfies the three core requirements. The first requirement is satisfied since the matrix format is agnostic to what kind of interactions are controlled in the system. The second requirement is satisfied since the matrix format allows introduction of new roles and there is fundamentally no fixed number for rows. The third requirement is satisfied since multiple interaction activities can be active in any channel and each interaction activity state can be controlled independently. The core framework is implemented as a functional live audience interaction management system called Presemo (version 4) (Chapter 6). The evaluation of the design of Presemo reveals more detailed fivetier structure for the control of interaction activities . The interaction activity control levels in LAIX-score design framework are (1.) creation and deletion, (2.) state control matrix, (3.) interaction pattern specific control, (4.) content management and (5.) presentation management. Presemo is limited implementation of the framework since the basic version supports only four interface channels. Presemo is a commercial level system and it has been utilized in thousands of live audience interaction situations and we have used it to produce more than 100 live audience interaction productions. The research investigates four case studies in more detail (Chapter 7). These four case studies are produced in different environments and this way demonstrate the generic qualities of Presemo and the LAIX-score design framework. One of the case study production focuses on professional event productions, another in application of Presemo in University context, third one focuses on use of live audience interaction in large scale computer-supported workshops and fourth one presents use of live audience interaction techniques in a pervasive adventure designed for K 12 students. The case studies validate the three core requirements and identifies 11 new additional requirements for the LAIX-score matrix. The case studies also reveal a more detailed interface channel structure. The revised LAIX-score design framework divides interface channels in three groups: organizer channels, audience channels and screen channels. Organizer channels combines performer and orchestrator roles, since these are roles that have some kind of control over interaction activities. Audience interface channels can be divided in groups. Screen channels are public channels whereas organizer and audience channels are personal channels. The 11 new requirements are further elaborated as two new core elements of the LAIX-score framework (Chapter 8): temporal management and identity management. Temporal management is divided in three parts; the functional cue list realizes the future temporal management, state control matrix realizes the real time management, and the production log realizes the management of past events. Identity management core element can be visualized as a table that lists all identities on one axis and different identity parameters on another axis. The study has identified six different types of identity attribute categories: identifiers, group membership, access rights, privacy settings, other identity and profile parameters and score attributes used for gamification. Identity attributes and privacy settings are used to manage identity parameters in order to achieve privacy and anonymity, which are important characteristics for most live audience interaction productions. Case studies have shown also that gamification is an important feature for live audience interaction. The core objective of the research is to create a framework for live audience interaction that could be generic and practical. As uch, the study is directly relevant extensive case reference of a live audience interaction system researchers and live audience interaction producers. The framework is adequately described so that any developer can utilize it in their own live audience interaction system designs. Methodologically the research has some areas of improvements mainly due to challenges in organizing data collection in demanding production environments (Section 9.3). These problems are common for in the wild research. The strengths of this research are extensive coverage of the live audience interaction domain and concrete validation of the framework as a production level implemented software system. While we have been developing the LAIX-score framework we have also identified several other research topics for live audience interaction (explained in Section 10.3) that are beyond the scope of the LAIX-score framework. There are for example several issues related to human and organizational factors of live audience interaction that are not covered in the LAIX-score framework, which is designed for the development of the computer system and production practices. These other research topics demonstrate how live audience interaction domain is still emerging domain with many interesting research possibilities. During the study, we have been involved in commercial development of live audience interaction. The business and marketing development (Section 10.4) will most probably be the driving force for the development of new interaction patterns, live audience interaction production formats, professional practices and generally new applications for live audience interaction. The further business and marketing development will define how organizations can adopt live audience interaction techniques and integrate them in to their communication and participation processes. The study proposes that standards organization would start defining protocols for live audience interaction. Details of wider adoption will ultimately define what kind of further research is relevant and feasible in the live audience interaction domain. The five core elements of the LAIX-score are integrated to each other and together they compose a comprehensive framework that can be used as design guideline for generic live audience interaction system (LAIMS). A LAIMS that is based on LAIX-score can host modularly different kinds of interaction patterns (Section 10.2). Modular approach can be also called s interaction agnostic approach. The modular approach may have several implications: modular approach makes development of new interaction patterns easier, support event productions that host different live audience interaction approaches, support sustainable system evolution and establishment of management practices for live audience interaction productions